21 citations · 24 across the 3 of their papers we have counts for
5 papers
Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging
Il Yong Chun, Dongwon Park, Xuehang Zheng +2
Regression that predicts continuous quantity is a central part of applications using computational imaging and computer vision technologies. Yet, studying and understanding self-su…
Learned Multi-layer Residual Sparsifying Transform Model for Low-dose CT Reconstruction
Xikai Yang, Xuehang Zheng, Yong Long +1
Signal models based on sparse representation have received considerable attention in recent years. Compared to synthesis dictionary learning, sparsifying transform learning involve…
BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization
Il Yong Chun, Xuehang Zheng, Yong Long +1
Obtaining accurate and reliable images from low-dose computed tomography (CT) is challenging. Regression convolutional neural network (CNN) models that are learned from training da…
Two-layer Residual Sparsifying Transform Learning for Image Reconstruction
Xuehang Zheng, Saiprasad Ravishankar, Yong Long +2
Signal models based on sparsity, low-rank and other properties have been exploited for image reconstruction from limited and corrupted data in medical imaging and other computation…
Low Dose CT Image Reconstruction With Learned Sparsifying Transform
Xuehang Zheng, Zening Lu, Saiprasad Ravishankar +2
A major challenge in computed tomography (CT) is to reduce X-ray dose to a low or even ultra-low level while maintaining the high quality of reconstructed images. We propose a new…